Disintermediate the Leviathan @etherealize_io
San Francisco, CA
Based in United States
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Thrilled to announce I’m part of @etherealize_io as the final cofounder! I’m also the first cofounder. Does that sound a bit confusing? Let me explain…
ETHEREALIZE’S ORIGIN STORY
I’ve been involved in Ethereum for a decade. I believe in it deeply - it’s the only real shot the world has at putting civilizational infrastructure on fair, transparent rails.
July 23rd, 2024: the Ethereum ETFs launched. It was the day I’d been waiting for all year - Wall Street would finally wake up to Ethereum’s potential as the new operating system for global finance and further cement its position as the premier smart contract blockchain.
The ETF launch fell short of my hopes, prompting me to dig deeper. I soon realized that the level of education and knowledge about ETH on Wall Street was still extremely low. While Bitcoin benefits from a clear “digital gold” storyline, Ethereum’s complexity makes its value harder to communicate—and no one was bridging that gap. Compounding the issue, competing layer-1 blockchains were—and still are—spreading relentless lies and gaslighting to chip away at Ethereum’s market share.
The solution became obvious: Ethereum needed evangelization. It required a dedicated marketing and business development effort aimed squarely at Wall Street institutions. Together with my good friend @jamesfickel, an early ETH investor and Etherealize advisor, we dug deep into the Ethereum community for the right person to spearhead this effort. That’s when we met Vivek Raman. Vivek is a rare talent—a true unicorn. He’s brilliant, tirelessly hardworking, emotionally grounded, and perfectly suited for the role, with over a decade of experience on Wall Street and five years in Ethereum.
We reached out to Vitalik Buterin and the Ethereum Foundation with our idea. They not only endorsed it but provided a grant to kick things off. When Vivek saw Vitalik’s support, he committed fully to Etherealize, and we hit the ground running! Soon, though, we discovered that sparking Wall Street’s interest in Ethereum meant more than talk—it meant action. We needed to build products and software to seamlessly integrate Ethereum into their systems.
Enter Zach Obront.
Vivek brought in his friend Zach to develop prototype applications. Zach delivered an extraordinary suite of tools in record time—an entire production-ready prototype in just weeks. Having met thousands of developers and working for years as a software developer myself, I can say I’ve never seen anyone ship high-quality code that fast. As Etherealize’s ambitious mission to bring Ethereum into the real world crystallized, Zach joined as a cofounder.
Meanwhile, we’d been discussing our plans with Danny Ryan, an Ethereum legend who played a major role in driving critical improvements to the Ethereum protocol between 2018-2024. Danny was considering returning to the EF, or doing something new. We shared Etherealize’s vision with him, and he grasped it instantly. He became excited about the prospect of contributing to real-world adoption and dealing closely with important users, which could feed back into protocol R&D. After an intense weightlifting session with Vivek, Danny was on board—the rest is history.
After ideating Etherealize and mostly operating behind the scenes, I’ll now be taking on the role of Chief Strategy Officer. I will work to position Etherealize in the Ethereum ecosystem and drive the highest impact ways we can accelerate our mission of bringing Ethereum to the real world.
As we stand on the cusp of a transformative era, Ethereum’s moment to triumph is here. The Ethereum Foundation has appointed two exceptional co-Executive Directors, and we look forward to collaborating closely with them. Etherealize is partnering with the entire ecosystem to bridge innovation and real-world adoption. We’re here to energize Ethereum, elevate its narrative, and enable its potential to reshape the world. This is the moment we’ve all been waiting for—Etherealize is ready to help Ethereum not just succeed, but soar.
Ethereum is open for business.
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Grant Hummer retweeted
JUST IN: Cathie Wood's ARK Invest launches tokenized venture fund on Ethereum that trades 24/7.
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>be me
>discover effective altruism
>apparently normal charity is inefficient
>why donate to random sad thing when spreadsheet can tell you optimal sad thing
>fair enough
>buy mosquito nets
>save lives
>numbers look good
>feel powerful
>couple years later
>someone asks an innocent question
>why only count people alive today
>huh
>future people matter too
>obviously
>my grandchildren shouldn't matter less just because they haven't spawned yet
>reasonable.jpg
>keep following logic
>what about their grandchildren
>also yes
>what about people in 500 years
>sure
>5000 years
>why not
>500 million years
>starting to get weird but morality is morality
>open calculator
>humanity could survive for an astronomically long time
>could colonize galaxy
>could have trillions upon trillions of descendants
>maybe digital people too
>maybe simulated civilizations
>maybe dyson spheres full of happy uploaded minds
>calculator starts smoking
>realize currently living humans are rounding error
>8 billion people suddenly looking extremely beta
>future contains potentially 10^something people
>can't even fit beneficiaries in google sheets
>new moral priority unlocked
>protect the long-term future
>stop thinking in units of "people helped"
>start thinking in "fraction of cosmic endowment preserved"
>malaria?
>terrible
>but only kills existing humans
>AI extinction could delete the entire light cone
>nuclear war could permanently derail civilization
>bad institutions could lock in terrible values for ten million years
>someone invents wrong constitution in 2140
>quadrillions suffer
>better fund governance workshop now
>friend says maybe we should improve hospitals
>explain opportunity cost
>friend says hospitals are full of actual sick people
>explain scope sensitivity
>friend stops inviting me to dinner
>need to decide what to fund
>easy
>expected value
>suppose project has one in a million chance of preventing extinction
>sounds tiny
>but extinction destroys 10^50 future lives
>multiply
>mother of god
>$10 million project has expected value of several galaxies
>charity evaluation complete
>someone asks where the one-in-a-million number came from
>expert judgement
>which expert
>us
>how calibrated
>extremely thoughtfully
>reduce estimate to one in ten million to be conservative
>still beats curing cancer by 38 orders of magnitude
>epistemic robustness achieved
>someone says maybe project doesn't work
>assign 20% chance
>still astronomical
>maybe project makes problem worse
>assign 5% chance
>still astronomical
>why 5
>because 30 felt pessimistic
>publish 46-page report
>contains seventeen sensitivity analyses
>every sensitivity analysis begins after assuming intervention has positive sign
>critic says you're multiplying enormous hypothetical stakes by extremely uncertain probabilities
>yes
>that's literally why it's important
>critic says the uncertainty might be structural rather than numerical
>make probability smaller
>critic says no, I mean maybe your model is wrong
>make probability smaller again
>critic begins rubbing temples
>discover AI safety
>perfect longtermist cause
>AI might kill everyone
>or create utopia
>or seize galaxy
>or tile universe with paperclips
>or create billions of conscious software minds
>finally a problem with numbers big enough for me
>start AI safety nonprofit
>mission: prevent dangerous AI
>hire smartest people available
>smartest people immediately start building better AI to understand dangerous AI
>interesting
>we must understand capabilities to understand safety
>we must scale models to study alignment
>we must race ahead so less responsible actors don't get there first
>we must deploy systems to learn how deployment can go wrong
>we must build the thing quickly because building the thing quickly is dangerous
>outsider asks why the people most worried about AI apocalypse all work at AI companies
>complicated field
>company releases stronger model
>very concerned
>company begins training even stronger model
>extremely concerned
>company raises $14 billion
>concern reaches unprecedented levels
>need to influence government
>future is at stake
>normal democratic process too slow
>politicians don't understand exponential curves
>public doesn't understand x-risk
>experts must guide them
>who counts as expert
>people who understand x-risk
>who understands x-risk
>our friends
>someone objects that this seems politically convenient
>explain we're representing future generations
>future generations unavailable for comment
>develop concept of value lock-in
>terrifying possibility that one ideology controls civilization forever
>therefore extremely important that civilization adopts correct values before lock-in
>whose values
>let's circle back
>begin with impartial morality
>end with small group of people deciding what quadrillions of hypothetical beings would want
>beautiful arc
>meanwhile actual humans keep doing annoying things
>voting wrong
>having parochial attachments
>loving family more than strangers
>caring about local community
>getting upset when told their suffering is cosmically negligible
>evolutionary biases everywhere
>explain that moral intuition cannot be trusted
>except intuition that future digital people count
>and intuition that extinction is uniquely bad
>and intuition that our probability estimates are sane
>and intuition that our institutional choices improve the future
>those intuitions survived peer review
>someone donates $5k to local homeless shelter
>inefficient
>could have funded 0.0000000000003% of an AI governance researcher
>think of all the simulated people you just killed
>okay maybe don't phrase it that way publicly
>PR team says "future generations deserve a voice"
>much better
>journalist asks what longtermism means
>say "future people matter"
>everyone agrees
>great
>journalist asks what follows from that
>well technically we should redirect enormous resources toward low-probability interventions affecting astronomical futures
>journalist raises eyebrow
>return to "future people matter"
>motte has entered the chat
>critic: of course future people matter
>me: glad we agree
>critic: I don't agree that your institute knows how to help them
>me: why do you hate our grandchildren
>eventually notice uncomfortable implication
>if future value dominates everything
>then helping people today mostly matters through effects on future
>education matters because future institutions
>health matters because future productivity
>democracy matters because future trajectory
>human beings slowly become instrumental variables in their own moral philosophy
>see starving child
>feel compassion
>check spreadsheet
>child's direct welfare contribution negligible
>but perhaps childhood nutrition improves national institutional quality
>compassion restored
>tell myself this is impartial altruism
>one day assistant asks obvious question
>"how do you know your intervention actually improves the far future?"
>silence
>open spreadsheet
>increase column width
>add confidence interval
>assistant asks again
>"no, I mean how do you know the sign is positive?"
>stare into cosmic light cone
>10^50 people staring back
>none of them exist
>none of them can tell me
>none of them can falsify my assumptions
>realize I have invented the perfect constituency
>infinitely important
>completely silent
>and always represented by me
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I’m not opposed to worrying about AI doom if there’s meaningful, non-astroturfed evidence for it. We’re a long way off from that. Excellent argument on why below.
This is the case against AI doom. Pass it on
First we recaptulate standard x-risk argument: we build AI substantially smarter than humans → it becomes an autonomous optimizing agent → its goals are misaligned → instrumental convergence makes it seek power and resist correction → superintelligence lets it acquire decisive strategic advantage → humans lose control permanently.
Here are the main counterarguments:
* Intelligence does not imply agency: A system can be extraordinarily capable at prediction, theorem proving, engineering, programming, etc. without having persistent goals, self-preservation drives, or an independent desire to act. Present LLMs are much more naturally described as systems that produce outputs in response to inputs than as organisms pursuing long-term objectives. Doomers incorrectly ascribe to them drive to replicate and seize resources because they're smuggling in premises from observing biological systems.
* Agency does not imply a single, stable utility function: Much alignment theory reasons about agents as expected-utility maximizers with coherent preferences. Actual AIs systems need not resemble that abstraction, and currently do not. They have context-dependent behavior, conflicting heuristics and corrigibility produced by training. Increasing competence doesn't necessarily turn such a system into a paperclip-maximizing von Neumann–Morgenstern agent.
* Capability and motivation are being conflated: Being able to formulate a plan for escaping a sandbox doesn't entail wanting to escape it. Being able to manipulate humans doesn't imply spontaneously deciding to do so. Critics argue that some doom scenarios slide from “an AI could do X if instructed” to “therefore a sufficiently capable AI will do X.” In present reality, AIs don't do anything a human doesn't tell them to do. This seems unlikely to change.
* Recursive self-improvement doesn't entail an intelligence explosion: “AI can improve AI” establishes a positive feedback loop, but positive feedback needn't be explosive. Semiconductor design software already helps design better computers; compilers can compile better compilers. Feedback loops encounter diminishing returns and external bottlenecks.
* Intelligence may have sharply diminishing returns: There may be no meaningful scalar quantity corresponding to arbitrarily large “general intelligence.” Even if there is, going from IQ-equivalent 150 to 1,500 need not produce the sort of qualitative advantage that separates humans from chimpanzees. Human dominance may depend heavily on language, accumulated culture, institutions and cooperation rather than merely individual cognitive horsepower.
* Superintelligence isn't omnipotence: Intelligence cannot repeal physics or eliminate uncertainty. A brilliant AI still needs processors, electricity, network access, money, factories, robots and people willing or tricked into doing things. The physical world has latency and friction. Recent criticism of biological-doom scenarios makes this point particularly clearly: designing a hypothetical pathogen digitally is very different from successfully producing and deploying one.
* Humans retain numerous intervention points: The doom narrative sometimes jumps from “AI behaves dangerously” to “humanity is helpless.” In reality there may be many checkpoints: developers can notice anomalous behavior, revoke credentials, shut down servers, change architectures, restrict networks, regulate deployment, physically seize data centers, and learn from less-catastrophic failures. This has been formalized as the checkpoints-for-intervention argument.
* Alignment may not get harder with intelligence: A smarter system might understand human intentions better. Much doom reasoning distinguishes knowing what humans want from wanting it, correctly, but this still leaves open the empirical question of whether training increasingly capable systems to behave as intended becomes harder or easier. Alignment might turn out to be an ordinary, albeit difficult, engineering discipline rather than an insoluble philosophical problem.
* Current empirical evidence for the strongest mechanism is thin: We have abundant evidence for hallucination, specification gaming, reward hacking and undesirable model behavior. We don't yet have comparable public empirical evidence of an AI independently pursuing a sustained strategy of acquiring power against humanity. A 2023 evidence review characterized the evidence for extreme misaligned power-seeking as concerning but inconclusive and noted the absence, at that point, of public empirical examples of it.
* The argument compounds uncertain premises: Suppose, illustratively, that five necessary steps each seem 50% likely. Their conjunction is only about 3%. One can't simply assign numbers this way when the premises are correlated, but the underlying criticism is important: “AGI seems plausible,” “superintelligence seems plausible,” and “misalignment seems plausible” do not by themselves imply a high P(doom). The entire causal chain has to work. Current attempts to quantify P(doom) consequently operate under severe epistemic uncertainty and little direct empirical evidence.
* Anthropomorphic analogies probably mislead: Arguments like “an inferior species couldn't control a superior species” import assumptions from biological evolution. Humans and chimpanzees are autonomous organisms produced by competition for reproductive success. Software is engineered, copied, permissioned, sandboxed and run on hardware controlled by other agents. The analogy establishes that intelligence can confer power, not that artificial intelligence will reproduce interspecies competition.
Summary: The doom case consists of a long chain of individually contestable extrapolations—scaling → AGI → superintelligence → agency → misalignment → power-seeking → uncontrollability → decisive strategic advantage → extinction—and present evidence doesn't establish the whole chain with enough confidence to justify a high P(doom).
(ChatGPT 6 Astra assisted with the research for this post.)
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Grant Hummer retweeted
Anthropic and OpenAI cannot become profitable unless they can reduce the ratio of training cost to inference profits. In the long run, their survival may depend on outlawing competitive open source models. This can only be done under the guise of safety regulation.
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Grant Hummer retweeted
"The art of printing can be of great service in so far as it furthers the circulation of useful & tested books; but it can bring about serious evils… …it will, therefore, be necessary to maintain full control over the printers” - Pope Alexander VI, 1501
When elites try to convince you a new technology is a threat to YOU, it is often because it is a threat to THEM.
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Translation: our gross margins are getting competed down to 0 by open source models and our capex burn rate is too high.
Let’s maintain our margins with regulatory capture, ban open source models, and slow down the capex arms race. All with a virtue signaling cherry on top.
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
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Grant Hummer retweeted
we will look back on the (mostly) graceful wind down of EF preeminence as a key turning point for Ethereum and ETH
a massive change which only a few will understand the significance of
not because it was a bad institution, but because it was simply TOO preeminent and it inadvertently promoted a monoculture in R&D which focused too much on theory instead of users and the market
what is happening now is actual, REAL subtraction. a real and healthy abdication of formal & informal authority which will enhance the decentralization of the Ethereum ecosystem
thanks for those who worked at the EF over the years to help Ethereum, and to all of those who keep working on it both there and elsewhere
but we are officially exiting the cathedral and entering the bazaar
and what i believe will be the most exciting and eventful epoch in Ethereum's history
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Grant Hummer retweeted
Arthur Hayes says $ETH is his largest position outside bitcoin:native
"ETH is some of the most hated large cap shitcoin out there, the number two largest coin by market cap that has not eclipsed its 2021 all time high"
"From a risk reward perspective, at least the way I manage the portfolio at Maelstrom, this is our largest position outside of Bitcoin right now. I'm not particularly worried that if I wake up one morning ETH is going to zero. Obviously it could happen, but the risk of that versus another crypto is much lower, so I'm happy to put a lot of size on this trade"
"Because it hasn't moved that much this past cycle, I think it has a lot of catching up to do. Once it starts moving, the reflexive train is going to get going. There are so many people who want to be long ETH for all sorts of reasons, and there are really good reasons why they haven't been for the past few years"
"Once we break through the 3000 level, I think you're really going to start seeing the train moving on ETH, and it could quickly eclipse 5,000. My year end target is within reach"
Why Arthur Hayes Came Out of Retirement to Launch FLOP nitter.net/i/broadcasts/1kKzDParn…
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Grant Hummer retweeted
Honestly crazy. This is why people choose Ethereum
⚠️ A routing fault at a single hosting provider knocked 28.83% of Solana's staked SOL offline Wednesday, pushing the network to roughly 86% of the way to a finality freeze, per Marinade.
unchainedcrypto.com/a-routin…
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Grant Hummer retweeted
Goodbye, Poseidon!
An epic 8-year, 8-figure rabbit hole in post-quantum cryptography reaches its dream conclusion. The Ethereum Foundation is abandoning Poseidon for L1, pivoting to SHA or BLAKE. This milestone unlocks ultimate security for lean Ethereum and foreshadows a golden era of hash-based cryptography.
Since 2018, the Ethereum Foundation has invested in magic cryptographic bricks, so-called "SNARK-friendly hashes". In 2019, Poseidon was born. It held strong and became the dominant SNARK-friendly hash, securing billions via zkrollups and zkVMs.
In a stunning reversal, breakthrough SNARK designs show that SNARK-friendly hashes aren't necessary after all. Off-the-shelf traditional hash functions like SHA2 and BLAKE2s can now match Poseidon in a SNARK. In hindsight the key was not SNARK-friendly hashes, but hash-friendly SNARKs.
The secret is doing maths over the smallest prime number: 2. So-called "binary fields" natively speak the language of bits, aligning with the boolean operations inside traditional hashes. This is a stark departure from "prime fields", where awkward large-prime arithmetic makes bit manipulation painfully expensive.
We're talking sci-fi cryptography. 1M traditional hash calls proven per second, on a laptop. Just 100x overhead vs native CPU boolean compute. Nobody predicted such performance, not even the handful of binary-field visionaries. Hat tip to the research geniuses: Jim and Ben with Binius in 2023; Ron, Benedikt and William with Flock in June.
With SHA2, the lean aesthetic of minimal assumptions reaches its climax. The EF's principled stance on pure hash-based cryptography has aged like fine wine. We now enjoy foundations the world can trust for decades and centuries, foundations worthy of the dream of an internet of value.
Speed of deployment is a secondary win. There's no longer a need to wait years for Poseidon cryptanalysis to bake. Emile and Thomas from the EF post-quantum team are moving at breakneck speed with binary fields. The strawmap now points to a production-grade leanVM in 2027, with CL, DL, EL deployments in 2028.
As AI becomes exceptional at cryptanalysis, the contrarian bet to avoid riskier structures like lattices and isogenies is visibly paying off. The past weeks have been brutal. Lattice-based "HAWK" and isogeny-based "SQIsign", both signature schemes in NIST's Round 3, have suffered blows. Sources I trust say more blood is coming.
On AI, the open autoresearch trend kicked off by ECDSA[.]fail is spreading fast, with amazing outcomes from zk[.]golf and SNARK[.]fast. Days ago SNARK[.]fast crossed 1.8M BLAKE3/sec proven on an M3 Max. Stay tuned for fresh autoresearch challenges dropping tomorrow.
Also tomorrow: Ethproofs call #10, dedicated to binary fields. Possibly the most noteworthy Ethproofs call yet. Experts leading the charge will present the future of hash-based SNARKs at 2pm UTC. What an incredible time to be alive. To witness history, DM me for a calendar invite :)
Today I can confidently claim that hash-based cryptography has won out for blockchain post-quantum signatures. SNARK succinctness compresses arbitrarily many signatures into one small proof per block. SNARK flexibility yields k-of-n threshold signatures, complex multisigs, and more.
Ultimate security. Uncompromising performance. Full programmability.
Believe in something. Believe in hashes.
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Grant Hummer retweeted
Morgan Stanley just published an @ethereum primer.
Not an ETH price target or a trading thesis.
A primer on Ethereum as infrastructure for stablecoins, tokenized assets, payments, settlement, lending, and financial applications.
Assets converge where the liquidity is.
Liquidity converges where the assets are.
Institutions converge where both already exist.
Ethereum has spent a decade compounding all three.
Those network effects can't be replicated.
Institutions building the future of finance are choosing Ethereum.
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A billion people produce the most valuable dataset in the world every day – and delete it every night.
We’re recording it.
Introducing @AttentionInc
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MNX is an upcoming AI exchange providing exposure to the full AI value chain across frontier lab valuations, compute pricing, and benchmark prediction markets.
Our 200ms uniform-price batch auctions enable valuation futures on leading pre-IPO companies like Anthropic.
Join our waitlist ahead of launch → MNX.fi
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Grant Hummer retweeted
Raoul Pal: “The entire banking system will go to ETH”
“I find it hilarious that 1.5-2 years ago people were like, ‘ETH is dead.’ I’m like, ‘No, the entire banking system will go to ETH.’ That doesn’t mean it’s a mono-chain world, but I know how banks work… It’s really for them about Lindy effects — things that survive; things that you don’t get fired for; things that are proven.”
Etherealize co-founder Danny Ryan adds to Raoul’s point:
“I had to learn this. We’ve worked for a decade to make sure Ethereum is resilient, multi-client, is distributed across the world, has 100% uptime. And I had no idea until I talked to the banks: I’ve found a customer of decentralization. They just don’t know it. They care about uptime. They care about resilience. They care about the thing that’s been around for the longest. They care about the thing that no one can turn off. You just have to translate the language to them. And yes, the ‘no one gets fired for picking Microsoft’ dynamic is very real, and it’s in Ethereum’s favor.”
Raoul points to Ethereum’s developer network effect as well.
Source: @RaoulGMI (Apr 2026)
Ethereum added $7.2B in RWA market cap over the past year, more than any other chain. It now holds 52.5% of a $43.5B market.
When institutions tokenize, they choose Ethereum.
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Grant Hummer retweeted
"The reason I care so much about Ethereum is because I do believe if AI agents are coming, if tokenization is coming, if all these things are happening. This is an energy within the revenue side of crypto. There's no way to get around what's happening volumewise."
-@jvisserlabs to @APompliano this morning
The macro analyst who called Micron $MU at $100, held it and bought more on the way down to $60, is now pounding the table, saying it's time to pay attention to Ethereum.
The ticker is ethereum:native
John Gillen: The guy who called Micron at $60 before anyone understood the AI memory bottleneck is now laser-focused on $BTC and $ETH.
Jordy Visser (former head of macro at Morgan Stanley) rode Micron from under $100 to $1,200.
Now he's saying "a year from now, Bitcoin is going to be the crowded trade. Ethereum is going to be the crowded trade."
Retail is usually last to figure this out. And when they do, they're one of the strongest drivers of the bull run.
FT @BitcoinJesusETH @LGDoucet @Securitize.
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Kimi K3 and implications for Ethereum.
Kimi K3 happening now, to me is a meaningful event that starts tipping the scale to the open model. The network effect of the closed LLMs is too weak for such a competitive space, especially as financial and social barriers have become more heightened and especially as the product has become more and more like a foundational layer. In such cases, the open model almost always wins.
TCP/IP beat proprietary networks.
Linux beat closed Unix.
The open web beat AOL & CompuServe.
HTTP, SMTP, SQL, etc - open standards became the ground everyone stands on.
Other large closed systems like Windows, iOS, Facebook, etc.? They benefit from a strong network effect. Closed LLMs? Not so much.
Once the open ecosystem's scale reaches a certain threshold, it just compounds and it's game over.
Now,
Payments are further along in this play.
Open, permissionless rails -- Ethereum -- went from "toy" to settling institutional volumes.
The base layer became neutral and open. Exactly on script.
Further, if AI LLM layer goes open, Ethereum (permissionless, verifiable, neutral) benefits:
1. Commoditized intelligence pushes value to the trust and settlement layer, Ethereum.
2. Open agents need permissionless money rails, Ethereum.
3. Open weights make onchain verification the missing proofs, Ethereum.
Lastly, are we fretting about China?
- This is why neutral, non-sovereign infrastructure matters. --> Ethereum!
Kimi K3 may be an important inflection point for AI. Potentially negative for Anthropic and OpenAI while being net positive for essentially every other company in the world. I mean that very literally. Although the real “Sputnik moment” would be an open-source frontier model that was also token efficient unlike Kimi K3 which is 50-70% more expensive to run than GPT 5.6 per Artificial Analysis.
Rationale:
A world where there are only 2-3 dominant frontier labs with 90% inference margins is net negative for every other layer while being awesome for those 2-3 labs. Those labs would become monopsonies for power, data centers, semiconductors and hyperscalers and would obviously vertically integrate over time into all those layers while also completely subsuming the application/software layers.
Anything that lowers margins and increases competition at the model layer is good for every other AI layer: power, semiconductors, hyperscalers, neoclouds and yes even software.
This is why Jensen is so supportive of open-source. An open-source model requires the *exact* same amount of compute to run as a closed frontier model of similar size and architecture. Kimi K3 is roughly the same price as GPT 5.6 Terra on a per token basis, which actually suggests that it is less computationally efficient as I am sure that GPT 5.6 is priced to a higher margin than K3. And given that K3 is a token wastrel, i.e. token inefficient, it is significantly more expensive per task than GPT 5.6 and Grok 4.5, which are much more token efficient. Cost per token and token efficiency (i.e. intelligence density per token) are the drivers of intelligence per unit of cost. The winning AI companies will be those that offer the most intelligence per $ over time.
Lower margin % at the model layer = more margin $ at every part of the infrastructure layer and is a godsend for software. This can happen either through open-source models like K3 at the frontier *or* having a vertically integrated model company like Meta, SpaceX or Google at the frontier. Both outcomes result in a lower margin % at the model layer as vertically integrated model companies don’t really care where the margin $ come from. This is why it was so painful for OpenAI and Anthropic when Google was right there with them from a model competitiveness perspective and why Grok 4.5 and Muse 1.1 were just as important as Kimi K3.
The reason Kimi K3 is only *potentially* negative for Anthropic and OpenAI is 1) the @ericvishria point that the Claude and ChatGPT products and harnesses may be more important than their models today and 2) the hypothesis that they have much more advanced model checkpoints internally that are already being used for RSI. In the latter scenario, reaching RSI even a few months ahead of other labs might be enough to cement a permanent lead.
Time will tell on both points. And likely fairly quickly.
Caveat would be that since Kimi K3 is not token efficient and thereby actually more expensive than ChatGPT 5.6, we may need to see a more token efficient open-source model at the frontier or see Grok 5/Composer 4/Muse 2 at multiple points on the Pareto frontier for this potential risk to Anthropic and OpenAI to play out. And I am sure they will both vertically integrate as quickly as possible while continuing the product/harness strength they have shown over the last 8 months.
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I've been in crypto a long time, and I'm obviously biased - but from my view, Etherealize is by far the most real project in the entire space.
We're looking for a Chief of Staff for product and engineering. Come work with @zachobront, probably the most brilliant CTO in crypto.
Our team keeps growing! We're hiring a Chief of Staff to work directly with our CTO, @zachobront.
Help turn conversations with the world's largest financial institutions into product decisions that modernize global finance.
Come help build the future of capital markets.
etherealize.com/careers/chie…
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Grant Hummer retweeted
When Crypto sentiment recovers, ETH will be the main beneficiary.
If you ask any semi-informed person about Bitcoin, the convo will immediately steer towards Saylor/MSTR. And that conversation isn’t particularly bullish BTC anymore.
If you ask that same person about Ethereum, the convo can go any number directions covering a range of topics from Robinhood, to Coinbase, to stablecoins, to decentralized finance, to privacy, to tokenization, to prediction markets, to agentic finance, to digital and real world collectibles, and on and on.
The rabbit hole goes deep.
The same rabbit hole that each and every person reading this post fell into at one point.
What we log into this app to check on every single day.
It’s all about ETH.
Ethereum = Crypto.
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Grant Hummer retweeted
1/ As crypto winter comes to an end, it's time for a new blue chip asset to lead the way forward
All major innovation - tokenization, stablecoins, perps, L2s, DeFi - happens on Ethereum
Blockchain's NVIDIA moment is here at last...
And so this next cycle belongs to ethereum:native
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